“2024 Mobile AI Application Scenario Research Report” (PDF file) – AI Tutorial Materials | AI Toolset

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“2024 Mobile AI Application Scenario Research Report”. A comprehensive analysis of the current situation and development trends of the global and Chinese artificial intelligence markets is focused on the market structure, user behavior, application scenarios and future development directions of mobile AI applications. In 2024, the mobile AI market showed a clear trend of differentiation, and language model applications dominate.Bean wrapApplications such as Kimi Smart Assistant and Wen Xiaoyan performed outstandingly. Subdivided tracks such as smart chat, image processing and smart tools are also developing rapidly, and user demand is accelerating its migration to mobile devices. The report deeply analyzes the user portraits of mobile AI applications, including users’ awareness of AI, usage scenarios, willingness to pay, and feedback on usage.

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AI Market Overview

Comparison of the artificial intelligence industry structure: Comparing the proportion of industries in AI applications, basic models, cloud infrastructure and chips in the United States and China.
Comparison of the development of AI in China and the United States: Showcase the proportion of China and the United States in the number of AI unicorn companies, AI companies, large models, etc., and predict the growth trend of the global generative AI market size.
Overview of China’s AI Industry: China’s AI industry has transformed from a hundred-model war to an application-driven one, and localized large models are being implemented at an accelerated pace, promoting the development of the AI application ecosystem. It introduces major domestic AI companies and software products, including representative products of traditional Internet companies, traditional AI companies and AI start-ups.

Mobile AI Market Research

Mobile AI track traffic growth is strong: The number of mobile AI independent devices doubled in 2024, the average monthly usage time continued to rise, and the market acceptance increased significantly.
User portrait: Overall user analysis of mobile AI applications: Analyze the core user characteristics of mobile AI applications, including gender, age, consumption capacity, city level and population tags.

Users’ awareness of AI and information acquisition channels: Users’ awareness of AI is constantly increasing, and social media and work and learning are the main sources of information. The time and opportunity for users to use AI have also been analyzed.
User behavior: feedback and usage opportunities brought by mobile AI products: Analyze the role of mobile AI applications in improving work efficiency, assisting search, providing accurate data, and the attractiveness of scenarios and functions of users starting to use AI.
User behavior: Tips for using mobile AI applications: Commonly used AI application techniques for users, such as Zhihu-style questions, iterative optimization, etc., as well as users’ interest in personalized use and basic principles of AI application.

User payment: willingness, payment range and method of mobile AI applications: Analyze users’ willingness to pay for mobile AI applications, payment ranges and payment methods, such as free basic version + value-added services, monthly subscription model, etc.
User payment: Factors that users value affect purchasing decision-making: Factors that users pay most attention to when purchasing mobile AI application services, such as convenience of use, diversity of functions, data privacy protection, etc.

User payment: awareness of advanced functions and willingness to pay: Users’ understanding of advanced functions of mobile AI, such as expert assistants, cloud collaboration, etc., and their willingness to pay for advanced functions.
Feedback: Problems encountered in the use of mobile AI applications: Users’ overall satisfaction with mobile AI applications and problems encountered during use, such as inaccurate answers and unnatural dialogues, etc., and areas that need improvement include integration with office software, accuracy of content generation, etc.

Research on the mobile AI segmentation track

Mobile AI application: User behavior of language model segmentation track: Analyze the user behavior of language model applications, such as the active user scale and growth trend of applications such as Doubao, Kimi Smart Assistant, Wen Xiaoyan, etc., as well as the core functional needs of users for these applications.
Mobile AI application: user behavior of intelligent chat segmented track: User demand for smart chat applications is growing rapidly. Hoshino APP stands out with its innovative AI social experience, and users pay more attention to pan-entertainment applications.

Mobile AI application: user behavior of image processing segment track: User stickiness in the image processing field continues to increase, leading applications such as Unbounded AI and Tuqu AI meet user needs through differentiated functions, and the traffic in segmented tracks has growth potential.
Mobile AI applications: Smart tools segment the user behavior of track: Although the user base of smart tool tracks is small, it has grown rapidly. Products launched by leading Internet companies such as Tencent Yuanbao meet user needs.

Research on mobile AI application scenarios

Main usage scenarios of mobile AI applications: Analyze the proportion and time proportion of users using mobile AI products in four major scenarios: life, work and study, entertainment and leisure, and parent-child education.
User portrait of mobile AI application main scenarios: Shows the characteristics of users’ gender, education, city level, income, occupation and other characteristics in different scenarios, such as the proportion of high-education and high-income populations in parent-child education scenarios.

Mobile AI application usage cycle, frequency and duration: Analyze the cycle, frequency and single use duration of users using mobile AI applications in each scenario, such as the frequency of use of parent-child scenarios is higher.
Experience of using the main scenarios of mobile AI applications: Users’ overall evaluation of mobile AI applications, as well as the most recognized and useful functions in different scenarios, such as collaboration with office software, entertainment and leisure functions, etc.

Future prospects for AI applications

Technology innovation drives user experience upgrade and deep integration of scenes: With the improvement of algorithms and models, the accuracy of AI answers and the naturalness of dialogue are improved, localized AI capabilities are enhanced, privacy protection and response speed are improved, life and work learning scenarios are gradually deepened, office software collaboration capabilities are improved, personal expert assistants and cloud collaboration functions are enriched, and one-stop solutions are provided for popularization of vertical applications for highly educated users, and professional scenario services such as education and office are optimized.

The AI application ecosystem is improved and popularized, and the market releases growth potential: China’s AI software market scale continues to expand, the user scale growth rate is high, the market potential of new first-tier cities is large, regional service differences are narrowed, user activity and duration continue to increase, core channels such as social media are continuously built and optimized, the user education system is improved, and the AI application ecosystem is gradually improved.